PROCESS
In order to effectively utilize data to individualize instruction, states need to collect and manage data, and provide user-friendly access to the data for schools, administrators, teachers, and parents. A longitudinal student data system that collects data from Pre-K-12 enables stakeholders to:
• follow students’ academic progress
• determine effectiveness of specific schools and programs
• identify higher performing schools and learn from best practices
• evaluate the effect of teacher training on student achievement
• prepare students for success in rigorous high school courses and college (DQC 2006)

When developing a statewide longitudinal data system, SETDA supports the Data Quality Campaign’s (DQC) ten essential elements: (http://www.dataqualitycampaign.org/essential_elements.cfm)

1. A unique statewide student identifier. As students move from grade to grade and from district to district, this ID number will allow states to track the progress of every student over time, from kindergarten through grade 12.
2. Student-level enrollment, demographic and program participation information. This information will help measure which programs are helping students succeed. It also will help account for students who transfer from school to school and ensure that test data are disaggregated correctly.
3. The ability to match individual students' test records from year to year to measure academic growth. Being able to match test records for individual students from last year to this year will provide valuable diagnostic information to teachers and principals and will help educators monitor each student's academic growth.
4. Information on untested students. With this information, states can ensure that students from all groups are participating in state tests and account for students who were exempted from the tests.
5. A teacher identifier system with the ability to match teachers to students. Many states collect data on teacher education and certification, but matching teachers to students by classroom and subject is critical to understanding the connection between teacher training and qualifications and student academic growth.
6. Student-level transcript information, including information on courses completed and grades earned. States will be able to track course-taking patterns and analyze their relationship to success on state assessments and readiness for college and work.
7. Student-level college readiness test scores. Student performance on the SAT, SAT II, ACT, Advanced Placement, International Baccalaureate and other college readiness exams is a good indicator of whether students are prepared to succeed in postsecondary education and work. Some states are going a step further by building college readiness tests into their statewide assessment systems.
8. Student-level graduation and dropout data. A majority of states currently collect annual records on individual graduates and dropouts, but to calculate the graduation rates defined in the new National Governors Association compact, states need to be able to track individual students over time.
9. The ability to match student records between the P-12 and higher education systems. Opening lines of communication between P-12 and higher education is critical to ensuring that students succeed at the postsecondary level. Connecting student performance in college to what happens in high school will give high schools the information they need to align curriculum and instruction to ensure that graduates are better prepared for college and work.
10. A state data audit system assessing data quality, validity and reliability. The decisions made in education are only as good as the information on which they are based.

In developing a state longitudinal data system, states should take into account the following seven fundamental concepts identified by the DQC:

1. Privacy Protection - the assignment of unique student identifiers and the guarantee that personally identifiable data is not available to data users
2. Data Architecture - the documentation and enforcement of rules on how data is coded, stored, managed, and used
3. Data Warehouse – a storage area of data, such as student, staff, curriculum, facilities, and finance
4. Interoperability – the ability of different software systems for different vendors to share information without customized programming or data manipulation
5. Portability – the ability to exchange student transcript information electronically across districts and states or between P-12 and postsecondary systems
6. Professional Development around Data Processes and Use – the training of people charged with collecting, storing, analyzing, and using data
7. Researcher Access – the capacity and willingness to share data with researchers while meeting federal and state privacy regulations to enable research and evaluation studies

Source: Bergner, T. and Smith, N. (2007). How can my state benefit from an educational data warehouse? Data Quality Campaign. (ADOBE)